Triple
T17810473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tinker Air Force Base |
E444686
|
entity |
| Predicate | hasMilitaryWorkforce |
P14275
|
FINISHED |
| Object | active duty personnel |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: active duty personnel | Statement: [Tinker Air Force Base, hasMilitaryWorkforce, active duty personnel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMilitaryWorkforce Context triple: [Tinker Air Force Base, hasMilitaryWorkforce, active duty personnel]
-
A.
hasArmedForces
Indicates that an entity possesses or maintains organized military forces under its control.
-
B.
hasMilitaryBase
Indicates that one entity possesses, hosts, or contains a military base associated with or located on another entity.
-
C.
hasMilitaryPresence
chosen
Indicates that a military force is present in, stationed at, or operating within a particular location or entity.
-
D.
hasMilitaryStatus
Indicates that an entity possesses a specific military affiliation, role, or status (such as active duty, reserve, or veteran).
-
E.
USForceStrength
Indicates the level or magnitude of military forces deployed or available by the United States in a given context.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8b9f0de78819099395b14db75a8a6 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4887a50488190b9c148146ec607e6 |
completed | April 19, 2026, 7:47 a.m. |
| PD | Predicate disambiguation | batch_69e3d8de28688190844b65acf6af54e6 |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:14 a.m.